{"id":"https://openalex.org/W7138832189","doi":"https://doi.org/10.48550/arxiv.2603.17930","title":"Interpretable Traffic Responsibility from Dashcam Video via Legal Multi Agent Reasoning","display_name":"Interpretable Traffic Responsibility from Dashcam Video via Legal Multi Agent Reasoning","publication_year":2026,"publication_date":"2026-03-18","ids":{"openalex":"https://openalex.org/W7138832189","doi":"https://doi.org/10.48550/arxiv.2603.17930"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.17930","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17930","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.17930","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130159185","display_name":"Jingchun Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yang, Jingchun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129923346","display_name":"Jinchang Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Jinchang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5130159185"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.24719999730587006,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.24719999730587006,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.20649999380111694,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.13940000534057617,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5733000040054321},{"id":"https://openalex.org/keywords/accident","display_name":"Accident (philosophy)","score":0.46219998598098755},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.46160000562667847},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.45410001277923584},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.44190001487731934},{"id":"https://openalex.org/keywords/legal-document","display_name":"Legal document","score":0.42340001463890076}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6392999887466431},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5733000040054321},{"id":"https://openalex.org/C2780289543","wikidata":"https://www.wikidata.org/wiki/Q424630","display_name":"Accident (philosophy)","level":2,"score":0.46219998598098755},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.46160000562667847},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.45410001277923584},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.44190001487731934},{"id":"https://openalex.org/C2993995455","wikidata":"https://www.wikidata.org/wiki/Q3150005","display_name":"Legal document","level":2,"score":0.42340001463890076},{"id":"https://openalex.org/C17319257","wikidata":"https://www.wikidata.org/wiki/Q21189184","display_name":"Statute","level":2,"score":0.4196999967098236},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.4146000146865845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35839998722076416},{"id":"https://openalex.org/C2989506057","wikidata":"https://www.wikidata.org/wiki/Q9687","display_name":"Traffic accident","level":2,"score":0.3508000075817108},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3149999976158142},{"id":"https://openalex.org/C2993475605","wikidata":"https://www.wikidata.org/wiki/Q19926935","display_name":"Legal responsibility","level":2,"score":0.30169999599456787},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.27630001306533813},{"id":"https://openalex.org/C169437150","wikidata":"https://www.wikidata.org/wiki/Q8458","display_name":"Human rights","level":2,"score":0.2734000086784363},{"id":"https://openalex.org/C522695570","wikidata":"https://www.wikidata.org/wiki/Q6517578","display_name":"Legal research","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.26649999618530273},{"id":"https://openalex.org/C2775946814","wikidata":"https://www.wikidata.org/wiki/Q2497143","display_name":"Legal culture","level":2,"score":0.26589998602867126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.17930","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17930","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.17930","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17930","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.591066300868988,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"widespread":[1],"adoption":[2],"of":[3,96],"dashcams":[4],"has":[5],"made":[6],"video":[7,61,122],"evidence":[8],"in":[9,18],"traffic":[10,37,82,103,115],"accidents":[11],"increasingly":[12],"abundant,":[13],"yet":[14],"transforming":[15],"\"what":[16],"happened":[17],"the":[19,68,80],"video\"":[20],"into":[21],"\"who":[22],"is":[23],"responsible":[24],"under":[25,79],"which":[26],"legal":[27,49,76,127,153,167],"provisions\"":[28],"still":[29],"relies":[30],"heavily":[31],"on":[32,42,54,142],"human":[33],"experts.":[34],"Existing":[35],"ego-view":[36],"accident":[38,116],"studies":[39],"mainly":[40],"focus":[41],"perception":[43],"and":[44,58,89,99,124,136,144,152,165],"semantic":[45],"understanding,":[46],"while":[47,161],"LLM-based":[48],"methods":[50],"are":[51],"mostly":[52],"built":[53],"textual":[55,90,121],"case":[56],"descriptions":[57,91],"rarely":[59],"incorporate":[60],"evidence,":[62],"leaving":[63],"a":[64,74,93,110,114,126,163],"clear":[65],"gap":[66],"between":[67],"two.":[69],"We":[70],"first":[71],"propose":[72],"C-TRAIL,":[73],"multimodal":[75],"dataset":[77],"that,":[78],"Chinese":[81,102],"regulation":[83],"system,":[84],"explicitly":[85],"aligns":[86],"dashcam":[87],"videos":[88],"with":[92],"closed":[94],"set":[95],"responsibility":[97,132],"modes":[98],"their":[100],"corresponding":[101],"statutes.":[104],"On":[105],"this":[106],"basis,":[107],"we":[108],"introduce":[109],"two-stage":[111],"framework:":[112],"(1)":[113],"understanding":[117],"module":[118],"that":[119,130,147],"generates":[120],"descriptions;":[123],"(2)":[125],"multi-agent":[128],"framework":[129],"outputs":[131],"modes,":[133],"statute":[134],"sets,":[135],"complete":[137],"judgment":[138],"reports.":[139],"Experimental":[140],"results":[141],"C-TRAIL":[143],"MM-AU":[145],"show":[146],"our":[148],"method":[149],"outperforms":[150],"general":[151],"LLMs,":[154],"as":[155,157],"well":[156],"existing":[158],"agent-based":[159],"approaches,":[160],"providing":[162],"transparent":[164],"interpretable":[166],"reasoning":[168],"process.":[169]},"counts_by_year":[],"updated_date":"2026-03-20T20:54:20.808490","created_date":"2026-03-20T00:00:00"}
